Field of the Invention
The present invention broadly relates to a method for identifying cells based on their replication domain timing profiles using a high resolution genomic array. The present invention also broadly relates to a method for distinguishing cells from other cells based on replication timing profiles using a high resolution genomic array. The present invention further broadly relates to determining one or more replication timing fingerprints of a cell by comparing replication domain timing profiles obtained using a high resolution genomic array.
Related Art
Conventional mechanisms to classify or identify cells involve a variety of heterogeneous biochemical and molecular procedures. For example, morphology-based approaches (e.g., histology) rely on microscopic examination of cell shape and features to determine cell type. This approach is useful in cases in which cells display a distinctive shape (e.g., long axons in neurons) and/or an easily recognizable feature (e.g., a lipid vesicle stained for fats), but most cells are difficult to distinguish based on their appearance alone. Histology-based procedures to cell identification also require a highly trained person making them impossible to apply in a high-throughput manner.
Protein-based approaches, including biochemical and/or immunological techniques, involve detection of specific proteins that may indicate a particular cell type. A protein may be recognized by an antibody specific for such protein present either on the cell surface (e.g., by immunohistology) or in extracts or samples from disintegrated cells (e.g., by immunoblotting or ELISA). These assays are generally sensitive, fast and simple. However, because each antibody only recognizes one particular protein antigen, such approaches generally do not provide sufficient information to distinguish various types of cells. In other words, a single protein marker is rarely a guarantee of a particular cell type. On the other hand, larger scale protein detection methods (e.g., proteomics) suffer from insufficient sensitivity and a lack of capability for automation.
RNA-based approaches are based generally on the detection of mRNA as a reflection of gene expression that may be indicative of a particular cell type and may be performed individually or using an array system. See, e.g., Spellman et al., Mol. Biol. Cell 9:3273-97 (1998); DeRisi et al., Science 278:680-686 (1997); Burton et al., Gene 293:21-31 (2002). Indeed, these technologies can produce a great deal of information about the overall pattern of gene expression of a cell. However, the decisive drawback of this system is the instability of RNA. Every experiment with RNA must take into account possible degradation of RNA that may occur during sample collection, storage, and experimentation. This is especially problematic when working with archived samples (e.g., preserved biopsies) or with limited amounts of cellular material. A further problem with RNA-based approaches is that mRNA fluctuates in response to temporary changes in environmental conditions. In addition, it has been demonstrated recently that mouse embryonic stem cells (mESCs) display considerable cell-to-cell heterogeneity in the expression of certain pluripotency-specific marker genes. See, e.g., Silva et al., “Capturing pluripotency,” Cell 132:532-536 (2008); and Toyooka et al., “Identification and characterization of subpopulations in undifferentiated ES cell culture,” Development 135:909-918 (2008).
Therefore, RNA-based approaches for cell identification are limited by perturbations in gene expression caused by transient cell culture conditions, cell-to-cell heterogeneity in gene expression, and random degradation of mRNA in cell-derived extracts or samples that adversely affect the robustness, reproducibility, and interpretation of such techniques. As a result, biological and stochastic variability must be countered by intense bioinformatic analysis. In general, RNA-based arrays are useful discovery tools, but they are not yet widely applicable as a clinical or large scale assay method for the identification of cells. See, e.g., Miller et al., Cancer Cell 2:353-61 (2002); Nadon et al., Trends Genet 18:265-71 (2002); Murphy D, Adv Physiol Educ, 26:256-70, (2002).
In recent years, some markers for epigenetic modifications to chromatin, such as DNA methylation and histone acetylation, have been used to study and distinguish cells. Such approaches are based on the fact that higher organisms must impose and maintain different patterns of gene expression in various types of tissues and/or cells despite having essentially the same DNA sequence encoded by the genome of all cell types within the body of an individual. This is achieved largely through changes in chromatin structure caused in part by chemical modification of chromatin. Generally speaking, the most condensed chromatin domains, known as heterochromatin, are inaccessible to DNA binding factors and tend to be transcriptionally silent, whereas more extended chromatin domains, known as euchromatin, correspond to more accessible portions of the genome that tend to be transcriptionally active.
Therefore, assaying for various epigenetic modifications to chromatin within a collection of cells may provide a basis for distinguishing not only different types of cells, but normal versus transformed cells. For example, aberrant methylation of DNA frequently accompanies the transformation event from healthy to cancerous cells. Indeed, there are examples where specific methylation status may be used identify and/or distinguish various forms of cancer (see, e.g., Jones et al., Nature Genetics 21:163-167 (1999); Esteller et al., Oncogene 21:5427-5440 (2002); Laird et al., Nature Reviews Cancer 3:253-266 (2003)), as well as different stages and lineage commitments of normal cells (see, e.g., Attwood et al., CMLS 59:241-257 (2002)). However, these techniques based on epigenetic chemical modifications to identify cell states are limited by the fact that (1) they require very high resolution (200 bp nucleosomal units), (2) they reflect dynamic chromatin states that can change or become heterogeneous within a homogeneous cell type, (3) there is a large diversity of histone modifications that would need to be individually investigated to gain a comprehensive profile, and (4) these rely on the use of different and expensive antibodies and other reagents that would create challenges for high-throughput analysis.
Accordingly, new and improved methods for identifying and/or distinguishing cells are still needed.